Triple
T841967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disney's Art of Animation Resort |
E18196
|
entity |
| Predicate | hasThemeSection |
P6142
|
FINISHED |
| Object | Cars |
E46398
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Cars | Statement: [Disney's Art of Animation Resort, hasThemeSection, Cars]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cars Context triple: [Disney's Art of Animation Resort, hasThemeSection, Cars]
-
A.
Cars
chosen
Cars is a 2006 Pixar animated film that follows a hotshot race car who discovers friendship and humility in a forgotten desert town.
-
B.
Mobil
Mobil is a major American oil company and fuel brand that became part of ExxonMobil after a 1999 merger.
-
C.
Motor Mania
Motor Mania is a 1950 Disney animated short film featuring Goofy that humorously depicts the transformation of a mild-mannered driver into an aggressive road menace.
-
D.
Autoblog
Autoblog is an automotive news and review website known for its coverage of car industry news, vehicle reviews, and consumer car-buying information.
-
E.
California Cars
California Cars are bi-level intercity passenger railcars used primarily in California for corridor services such as the Amtrak Capitol Corridor.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a49389f44881909a608fb27d89f247 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2b66c908190a52f731119b77a1e |
completed | March 1, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7929a91088190bef474424bde527c |
completed | March 4, 2026, 2:02 a.m. |
Created at: March 1, 2026, 7:38 p.m.